list_curated

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully relies on text, and it clearly states that the tool lists every curated dataset ID and returns a sorted list. No hidden behaviors are indicated, though it could mention if there are any limits (e.g., maximum results), but the simple nature makes this sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no wasted words. The key action is front-loaded, and each sentence adds value: first the what, then the return format.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters and an output schema (indicated by context), the description is complete. It states the return type (sorted list of dataset IDs), which is all that's needed for this simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters, so the description does not need to explain them. According to guidelines, when there are 0 parameters, the baseline is 4 unless the description adds unnecessary information. Here it adds none, which is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List') and the resource ('curated dataset IDs'), adding scope ('every', 'in this version of apra-mcp'). This distinguishes it from siblings that describe, retrieve data, or search, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use this tool versus siblings like 'search_datasets' or 'describe_dataset'. Usage is only implied by the stated purpose, without any 'when to use' or 'alternatives' mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.